• Advances in Traditional Medicine
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• v.7 no.1
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• pp.51-64
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• 2007

Mucus is an aqueous gel complex with a constitution of about 95% water, high molecular weight glycoprotein (mucin), lipid, salts etc. Mucus appears to represent a significant barrier to the absorption of some compounds. Natural mucoadhesive agent was isolated and purified from the aqueous extract of the seeds of prosopis pallida (PP). Formulated tablet with the isolated material by wet granulation method. Some natural edible substances are in consideration for candidates as mucoadhesive agents to claim more effective controlled drug delivery as an alternative to the currently used synthetic mucoadhesive polymers. Subjected the materials obtained from natural source i.e. PP and standard synthetic substance, sodium carboxymethyl cellulose for evaluation of mucoadhesive property by various in vitro and in vivo methods. Through standard dissolution test and a model developed with rabbit, evaluated in vitro controlled release and bioadhesive property of theophylline formulation. Mucoadhesive agent obtained from PP showed good mucoadhesive potential in the demonstrated in vitro and in viνo models. The results suggest that the mucoadhesive agent showed controlled release properties by their application, substantially. In order to assess the gastrointestinal transit time in vivo, a radio opaque X-ray study performed in healthy rabbit testing the same controlled release formulation with and without bioadhesive polymer. Plasma levels of theophylline determined by the HPLC method and those allowed correlations to the in vitro mucoadhesive study results. Better correlation found between the results in different models. PP may acts as a better natural mucoadhesive agent in the extended drug delivery system.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.522-532
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• 2017

In this study, we propose a fault analysis method for a power distribution grid with PCS-based DERs. We first explain the characteristics of a PCS-based DER. According to the characteristics, the DER is considered as a current-controlled voltage source, which produces varying voltages within a certain limit so that currents equal to given references flowing from the DER to the grid (currents controlled). So, we introduce the symmetrical equivalent models in the form of varying voltage source for fault analysis and then, construct a convex optimization problem to solve the fault problem associated with the equivalent models and grid conditions. Thus, the proposed method enables to perform a proper fault analysis considering the characteristics of the DER, which are currents controlled, voltage limited, and unity power factor achievement. To verify the validity of the proposed method, we perform computer simulations with the proposed method and with MATLAB Simulink, and the results are compared.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07b
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• pp.1234-1238
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• 2004

A Controlled neural networks are proposed in order to measure nonlinear environments in adaptive and in realtime. The structure of it is similar to recurrent neural networks: a delayed output as the input and a delayed error between tile output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by backpropagation and each weights are updated by RLS(Recursive Least Square). Consequently, this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. This new neural networks is Error Estimated Neural Networks. We can estimate nonlinear models in realtime by the proposed networks and control nonlinear models. To show the performance of this one, we have various experiments. And this controller call prove effectively to be control in the environments of various systems.

• Journal of Power System Engineering
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• v.6 no.2
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• pp.73-81
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• 2002

In this study, electronically controlled automatic transmission adopted on a subcompact model in the market was modelled, and the driving performances of the transmission were simulated with the models. Kinetic and dynamic models of working components are established. The driving simulation program is developed with those models, and the various driving conditions are analyzed. With the results, the dynamic behaviour of the engine and the automatic transmission is easily understood. Especially, the transient performances of torque converter and clutches are deeply analyzed. Skipping the vehicle road test by using this analyzing tool, we can expect the cost down and the reduction of the development period of automatic transmission.

• Fire Science and Engineering
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• v.32 no.1
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• pp.7-15
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• 2018

The prediction performance of combustion models in the Fire Dynamics Simulator (FDS) were evaluated by comparing with experiment for compartment propane gas fires. The mixture fraction model in the FDS v5.5.3 and Eddy Dissipation Concept (EDC) model in the FDS v6.6.3 were adopted in the simulations. Four chemical reaction mechanisms, such as 1-step Mixing Controlled, 2-step Mixing Controlled, 3-step Mixing Controlled and 3-step Mixed (Mixing Controlled + finite chemical reactions) reactions, were implemented in the EDC model. The simulation results with each combustion model showed similar level for the temperature inside the compartment. The prediction performance of FDS with each combustion model showed significant differences for the CO concentration while no distinguished differences were identified for the $O_2$ and $CO_2$ concentrations. The EDC 3-step Mixing Controlled largely over-predicted the CO concentration obtained by experiment and the mixture fraction model under-predicted the experiment slightly. The EDC 3-step Mixed showed the best prediction performance for the CO concentration and the EDC 2-step Mixing Controlled also predicted the CO concentration reasonably. The EDC 1-step Mixing Controlled significantly under-predict the experimental CO concentration when the previously suggested CO yield was adopted. The FDS simulation with the EDC 1-step Mixing Controlled showed difficulties in predicting the $CO_2$ concentration when the CO yield was modified to predict the CO concentration reasonably.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.10
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• pp.947-954
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• 2013

This article focuses on a hemispherical resonator gyro driven by the Coriolis effect. The operational principle of resonator gyros and mathematical models are introduced. These models are useful to explain the behavior of a resonator and to design controllers. Several control tests of a resonator have been done. A resonator has been excited by electromagnets controlled by a computer. Its amplitude has been adjusted by a PI control. The transient response is matched with a simulation result based on a mathematical model. A vibrating pattern may drift due to non-uniform factors of a resonator. The drift of the vibrating pattern is controlled and aligned to a reference direction by a PI control. These results are very useful to understand the behavior of resonator gyros and to design advanced control algorithm for better performance.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.5
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• pp.677-684
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• 2008

Accurate estimation of dry matter intake (DMI) is a prerequisite to meet animal performance targets without penalizing animal health and the environment. The objective of the current study was to evaluate some of the existing models in order to predict DMI when lactating dairy cows were offered a total mixed ration containing a high level of concentrates and locally produced agricultural by-products. Six popular models were chosen for DMI prediction (Brown et al., 1977; Rayburn and Fox, 1993; Agriculture Forestry and Fisheries Research Council Secretariat, 1999; National Research Council (NRC), 2001; Cornell Net Carbohydrate and Protein System (CNCPS), Fox et al., 2003; Fuentes-Pila et al., 2003). Databases for DMI comparison were constructed from two different sources: i) 12 commercial farm investigations and ii) a controlled dairy cow experiment. The model evaluation was performed using two different methods: i) linear regression analysis and ii) mean square error prediction analysis. In the commercial farm investigation, DMI predicted by Fuentes-Pila et al. (2003) was the most accurate when compared with the actual mean DMI, whilst the CNCPS prediction showed larger mean bias (difference between mean predicted and mean observed values). Similar results were observed in the controlled dairy cow experiment where the mean bias by Fuentes-Pila et al. (2003) was the smallest of all six chosen models. The more accurate prediction by Fuentes-Pila et al. (2003) could be attributed to the inclusion of dietary factors, particularly fiber as these factors were not considered in some models (i.e. NRC, 2001; CNCPS (Fox et al., 2003)). Linear regression analysis had little meaningful biological significance when evaluating models for prediction of DMI in this study. Further research is required to improve the accuracy of the models, and may recommend more mechanistic approaches to investigate feedstuffs (common to the Asian region), animal genotype, environmental conditions and their interaction, as the majority of the models employed are based on empirical approaches.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.2
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• pp.191-202
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• 1998

An electronic-hydraulic controlled line pressure system was suggested based on the mechanical controlled CVT base model. As a high level control strategy, a 3-D optimal line pressure map was obtained considering the driver's desire, driving conditions. Also, PID type low level controller was designed. Using the high level control strategy and the dynamic models of the base model CVT with electronic controlled line pressure system, performance simulations were carried out. It is seen from the simulation results that fuel economy of the electronic controlled strategy keeps the line pressure low, which results in the improved efficiency of the hydraulic system.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.97-103
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• 2020

Wireless sensor networks collect and analyze sensing data in a variety of environments without human intervention. The sensor network changes its lifetime depending on routing protocols initially installed. In addition, it is difficult to modify the routing path during operating the network because sensors must consume a lot of energy resource. It is important to measure the network performance through simulation before building the sensor network into the real field. This paper proposes a WSN model for a low-energy adaptive clustering hierarchy protocol using DEVS kernel models. The proposed model is implemented with the sub models (i.e. broadcast model and controlled model) of the kernel model. Experimental results indicate that the broadcast model based WSN model showed lower CPU resource usage and higher message delivery than the broadcast model.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.23 no.2
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• pp.27-44
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• 2012

This paper provides suggestions for analyzing Cultural Objects Name Authority(CONA) developed by the Getty Trust and applying CONA to Functional Requirements for Subject Authority Data(FRSAD). CONA is linked with the other Getty controlled vocabularies such as AAT, ULAN, and TGN, and can be linked with the library controlled vocabularies, such as LCSH. However, CONA has differences with library models since CONA is based on the art museum or art gallery. Therefore, we need to consider it when we link CONA to library standard models. The results discussed in this study have implications for analyzing CONA which provides access for cultural objects and applying it to the FRSAD, the subject authority model in library fields.